---
license: apache-2.0
base_model: t5-large
tags:
- generated_from_trainer
datasets:
- glue
metrics:
- accuracy
model-index:
- name: t5-large_rte_dense_sp0_ar0
  results:
  - task:
      name: Text Classification
      type: text-classification
    dataset:
      name: glue
      type: glue
      config: rte
      split: validation
      args: rte
    metrics:
    - name: Accuracy
      type: accuracy
      value: 0.0
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->

# t5-large_rte_dense_sp0_ar0

This model is a fine-tuned version of [t5-large](https://huggingface.co/t5-large) on the glue dataset.
It achieves the following results on the evaluation set:
- Loss: 0.9322
- Accuracy: 0.0

## Model description

More information needed

## Intended uses & limitations

More information needed

## Training and evaluation data

More information needed

## Training procedure

### Training hyperparameters

The following hyperparameters were used during training:
- learning_rate: 5e-05
- train_batch_size: 8
- eval_batch_size: 16
- seed: 1
- gradient_accumulation_steps: 2
- total_train_batch_size: 16
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 20
- num_epochs: 5

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 0.6781        | 0.16  | 25   | 0.6834          | 0.5487   |
| 0.7041        | 0.32  | 50   | 0.6878          | 0.5523   |
| 0.689         | 0.48  | 75   | 0.6836          | 0.6065   |
| 0.6902        | 0.64  | 100  | 0.6630          | 0.5740   |
| 0.6458        | 0.8   | 125  | 0.5695          | 0.7112   |
| 0.5973        | 0.96  | 150  | 0.6138          | 0.6823   |
| 0.5697        | 1.12  | 175  | 0.5707          | 0.7581   |
| 0.4567        | 1.28  | 200  | 0.6558          | 0.7256   |
| 0.3796        | 1.44  | 225  | 0.4968          | 0.7870   |
| 0.3749        | 1.6   | 250  | 0.5082          | 0.8123   |
| 0.5187        | 1.76  | 275  | 0.4428          | 0.8123   |
| 0.4176        | 1.92  | 300  | 0.3940          | 0.8556   |
| 0.2678        | 2.08  | 325  | 0.4938          | 0.8484   |
| 0.0761        | 2.24  | 350  | 0.6533          | 0.8520   |
| 0.2082        | 2.4   | 375  | 0.5901          | 0.8484   |
| 0.4081        | 2.56  | 400  | 0.5939          | 0.8520   |


### Framework versions

- Transformers 4.33.2
- Pytorch 2.0.1+cu117
- Datasets 2.14.5
- Tokenizers 0.11.6